In Vitro Conditions for a Successful Biolistics transformation System of Pineapples (ananas comosus merr.), in 'Contributing to a Sustainable Future'

In order to develop an efficient and reliable biolistics transformation system for pineapples parameters need to be optimised for growth, survival and development of explants pre- and post transformation. We have optimised in vitro conditions for culture media for the various stages of plant and callus initiation and development, and for effective selection of putative transgenic material. Shoot multiplication and proliferation is best on medium containing MS basic nutrients and vitamins with the addition of 0.1 mg/L myo-inositol, 20 g/L sucrose, 2.5 mg/L BAP and 3 g/L Phytagel, followed by transfer to basic MS medium for further development. Callus production on leaf base explants is best on MS nutrients and vitamins, to which 10 mg/L of BAP and NAA each was added. Optimum explant age for bombardment is 17-35 week old callus, while a pre-bombardment osmoticum treatment in the medium is not required. By comparing several antibiotics as selective agent, it has been established that a two-step selection of 2 fortnightly sub-cultures on 50 μg/mL of geneticin in the culture medium, followed by monthly sub-cultures on 100 μg/mL geneticin is optimal for survival of transgenic callus. Shoot regeneration from callus cultures is optimal on medium containing MS nutrients and vitamins, 5% coconut water and 400 mg/L casein hydrolysate. Plants can be readily regenerated and multiplied from transgenic callus through organogenesis. Rooting of shoots does not require any additional plant hormones to the medium. A transformation efficiency of 1 – 3.5% can be achieved, depending on the gene construct applied.

Standardising bull breeding soundness evaluations and reporting in Australia

There is substantial variation in bull breeding soundness evaluation procedures and reports in Australia; the situation is compounded by difficulties in interpretation and the validity of many reports. In an effort to overcome this, the scientific literature was reviewed [Fordyce G. In: Fordyce G, editor. Bull fertility: selection and management in Australia. Eight Mile Plains, Australia: Australian Cattle Vets; 2002] and the needs of stakeholders were considered in preparing a manual, Evaluating and Reporting Bull Fertility [Entwistle KW, Fordyce G. Evaluating and reporting bull fertility. Eight Mile Plains, Australia: Australian Cattle Vets; 2003.] that outlined standards for assessing and reporting bull breeding soundness. A new recording and reporting system, called Bull Reporter, is based on standards from this manual and groups bull fertility traits into five summary categories: Scrotum, Physical, Crush-side Semen, Sperm Morphology, and Serving. The client will generally select which categories they wish to have included in the evaluation to suit their specific purposes. While there is adequate room for comments, the veterinarian is not required to make an overall judgment of whether the bull has normal capacity to sire calves under natural mating management, but ensures the standards for each selected category are met. Professional, standardised, easy-to-read reports are produced either electronically [Entwistle KW, Fordyce G. Evaluating and reporting bull fertility. Eight Mile Plains, Australia: Australian Cattle Vets; 2003.] or manually. A bull owner or their agent signs the certificate to affirm that bulls have not undergone procedures to rectify faults which may have otherwise caused them to fail the standards. An accreditation system for assessing sperm morphology was established because of its demonstrated relationship with pregnancy rates and because of the difficulties in achieving consistent and accurate assessments among laboratories. It is considered that Bull Reporter is applicable to beef and dairy bulls across all levels of management, genotypes and environments throughout Australia, with substantial potential for application elsewhere in the world.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

Integrating Rapid Phenotyping and Speed Breeding to Improve Stay-Green and Root Adaptation of Wheat in Changing, Water-Limited, Australian Environments

Temperatures have increased and in-crop rainfall decreased over recent decades in many parts of the Australian wheat cropping region. With these trends set to continue or intensify, improving crop adaptation in the face of climate change is particularly urgent in this, already drought-prone, cropping region. Importantly, improved performance under water-limitation must be achieved while retaining yield potential during more favourable seasons. A multi-trait-based approach to improve wheat yield and yield stability in the face of water-limitation and heat has been instigated in northern Australia using novel phenotyping techniques and a nested association mapping (NAM) approach. An innovative laboratory technique allows rapid root trait screening of hundreds of lines. Using soil grown seedlings, the method offers significant advantages over many other lab-based techniques. Another recently developed method allows novel stay-green traits to be quantified objectively for hundreds of genotypes in standard field trial plots. Field trials in multiple locations and seasons allow evaluation of targeted trait values and identification of superior germplasm. Traits, including yield and yield components are measured for hundreds of NAM lines in rain fed environments under various levels of water-limitation. To rapidly generate lines of interest, the University of Queensland “speed breeding” method is being employed, allowing up to 7 plant generations per annum. A NAM population of over 1000 wheat recombinant inbred lines has been progressed to the F5 generation within 18 months. Genotyping the NAM lines with the genome-wide DArTseq molecular marker system provides up to 40,000 markers. They are now being used for association mapping to validate QTL previously identified in bi-parental populations and to identify novel QTL for stay-green and root traits. We believe that combining the latest techniques in physiology, phenotyping, genetics and breeding will increase genetic progress toward improved adaptation to water-limited environments.

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.